When metal is present in an object to be imaged using magnetic resonance imaging (MRI), the metal may introduce a susceptibility effect that in turn produces a B0 field inhomogeneity, which may be referred to as ΔB0. ΔB0 disturbs the frequency encoding relationship in MRI. Disturbing the frequency encoding relationship may produce in-plane and through-plane artifacts that compromise reconstructed images. The artifacts may include distortions, pile-up, signal voids, and other distortions. MRI of regions of bodies where there are metal implants (e.g., hip joints, knee joints, dental implants, screws, plates) has been challenged due to the susceptibility effect. The susceptibility effect may cause significant local changes in the main magnetic field B0 and may also cause significant local changes in the radio frequency (RF) field B1. Changes in the B0 and B1 fields produce significant impacts on RF pulse performance.
Different conventional approaches have been applied to address the susceptibility effect caused by metal in magnetic resonance (MR) images. These conventional approaches may have used high bandwidth (BW) for slice selection and frequency encoding. Some conventional approaches include a view angle tilted (VAT) approach, a slice encoding for metal artifact correction (SEMAC) approach, and a multi-acquisition variable-resonance image combination (MAVRIC) approach.
SEMAC and MAVRIC attempt to reduce through-plane artifacts by sampling at different offset frequency windows. Different metals may have different properties and characteristics. For example, stainless steel generates a larger offset frequency spectrum than titanium. The offset frequencies spectrum may be determined by characteristics of the metals that are used. With SEMAC and MAVRIC, the number of encoding steps required to improve an imaging result varies directly with the size of the offset frequency spectrum. As the offset frequency spectrum increases, additional encoding steps may be required. Additional encoding steps may result in longer imaging times, which may be difficult for patients to tolerate, and which may reduce the number of patient imaging sessions that may be performed per day. Unfortunately, when a patient presents for imaging, the composition of their implant may not be known. Thus, the number of encoding steps that may be needed for these conventional approaches may be unknown, leading to an educated guess or other heuristic approach. When heuristics are employed, imaging time may be unnecessarily long when too many encodings are used or image quality may be compromised when not enough encodings are used.
FIG. 1 illustrates how metal in MRI introduces two kinds of artifacts or distortions. A piece of metal 120 is illustrated producing distortions both in-plane and through-plane (slice). An in-plane distortion 100 is caused by a distorted readout gradient that causes a pixel dislocation in the readout direction. A through-plane (e.g., slice profile) distortion 110 is caused by a distorted slice selection gradient. The presence of metal 120 in the field of view (FOV) causes local B0 field changes due to the susceptibility effect. The local B0 field changes are proportional to the B0 field strength and may be different for different types of metals. The presence of metal 120 in the FOV also causes local B1 field changes because metal 120 possesses different electro-magnetic properties than other materials (e.g., human tissue, animal tissue).
FIG. 2 illustrates how the susceptibility effect differs for different materials. The susceptibility induced by metals depends on the metal type, the metal shape, and B0. A plastic bar illustrated in MRI 210 provides a reference image that helps visualize the distortions caused by the susceptibility effect of metals. A titanium bar is illustrated in MRI 200 and a steel bar is illustrated in MRI 220. The distortions around the metal bars cause information around the metal part to be lost for clinical diagnosis. The distortions may cause signal voids, falsified hyper signal intensity, and other undesirable effects. Images having metal in the FOV may also exhibit distortion due to offset resonance. Additionally, images having metal in the FOV may not be able to suppress some fat signal. Thus, conventional approaches may have employed additional encodings, which caused longer imaging times. Since the number of extra encodings required may vary based on the material of the implant (e.g., stainless steel, titanium, chrome-moly alloy), and since the material of the implant may not be known, the number of additional encodings may be too high or too low.
FIG. 3 provides an MRI 300 of a hip having a metal implant where there has been no correction. MRI 300 shows that with no correction, diagnostic information is lost. FIG. 3 also provides an MRI 310 of a hip having a metal implant where there has been some correction using conventional techniques. While there has been some improvement in image quality, diagnostic information is still lost.
FIG. 4 illustrates how conventional approaches that use extra encodings to cover an offset frequency spectrum may take longer than necessary due to unnecessary encodings. The offset frequency encoding spectrum illustrated is too wide. A piece of metal 410 may produce distortions for a slice profile 400. Some extra encodings 420 may be useful on a first side of the slice profile 400 and other extra encodings 430 may also be useful on a second side of the slice profile 400. The extra encodings may be frequency encodings at a frequency other than the frequency used for slice 400. Rather than the slice profile being a regular shape (e.g., rectangle), distortion 412 may stretch, compress, or otherwise change the profile out of the regular shape. The extra encodings 430 may acquire signal that can be used to correct for or otherwise account for the distortion. The encodings 440 and 450 are outside the distortion area and thus may provide no extra signal from which a correction can be made. Since the distortion 412 may not be predictable before imaging, many extra encodings may be employed, some of which may be wasteful. For example, extra encodings 440 and extra encodings 450 may be unnecessary and waste time. Conventional approaches like high bandwidth excitation and readout VAT, SEMAC, and MAVRIC may use a pre-determined set of extra encodings to capture offset frequencies. The amount of extra encoding may be a heuristic or empirical practice that tries to account for metal type, size, shape, and other factors.
FIG. 11 illustrates a desired slice profile 1100 and a distorted slice profile 1120. A piece of metal 1130 has produced distortions of the slice profile 1120 at 1132 and 1134. At 1132, the slice profile has been compressed and at 1134 the slice profile has been widened and shifted.